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In satellite design and manufacturing, due to the influence of material properties, sandwich structure and equivalent algorithm, there is usually a significant deviation between the theoretical model and the actual physical prototype. To solve the issue, a new finite element model of satellite sailboard based on sandwich theory is constructed. The key parameters of the model are iteratively optimized by Lagrange optimization algorithm to improve its accuracy and reliability. The Lansos method is used to simulate the satellite sailboard model, and the comparison is made with the actual test model. The results show that the error of the modified model in the first six orders of frequency is less than 5%, which meets the modal correlation standard, and the modal assurance criterion (MAC) value is higher than 0.85. Compared with the uncorrected model, the first six frequency errors are reduced by 0.1%, 0.9%, 0.7%, 2.0%, 1.1% and 5.5%, respectively. At the same time, the MAC value of each mode increased by 1.9%, 3.2%, 1.2%, 2.6%, 13.1% and 27.1%, respectively. These findings show that the revised sailboard model is closer to the test model in terms of frequency and modal characteristics, while providing a higher level of accuracy and reliability. [ABSTRACT FROM AUTHOR]

As the survival rates for prostate cancer (PCa) have improved, there has been an increasing focus on the mental health of couples affected by this condition. There have been several couple‐based psychological interventions, and yet the impact of this treatment modality on the mental health of PCa patients and their spouses is unclear. Consequently, a systematic search was conducted in PubMed, Embase, Cochrane, LILACS, and Web of Science up to March 2023 for randomized controlled trials (RCTs) addressing the impacts of couple‐based psychological interventions on both PCa patients and their spouses. Besides, the Cochrane Risk of Bias Assessment Tool was employed to evaluate the methodological quality and potential bias of the included studies. Moreover, statistical analysis and meta‐analysis were performed utilizing Revman 5.4, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) was employed to assess the certainty of evidence. A total of nine RCTs were included, utilizing anxiety, depression, distress, communication, and self‐efficacy as outcome indicators to assess mental health. Results demonstrated that couple‐based psychological interventions increased spouses' self‐efficacy (WMD, 0.21; 95% CI: −0.00 ~ 0.42; P = 0.05) and communication (SMD, 0.34; 95% CI: 0.09 ~ 0.59; P = 0.009), while reducing their distress (SMD, −0.21; 95% CI: −0.40 ~ −0.02; P = 0.03). Nonetheless, there is a need for additional research on the effect of couple‐based psychological interventions on the mental health of PCa‐affected couples given the limited evidence supporting this conclusion. [ABSTRACT FROM AUTHOR]

An experimental study was conducted to investigate the phenomenon of UAV attitude instability caused by large vibrations affecting single‐rotor UAV airborne equipment. Appropriate measurement points were selected to collect vibration signals from the unmanned aerial platform during takeoff and flight of the drone. The time‐domain response and power spectral density of the unmanned aerial platform were then obtained. Establish a dynamic model of the vibration reduction system for an unmanned aerial platform and design a two‐stage vibration reduction structure for the unmanned aerial platform. Through field flight tests of unmanned aerial vehicles, it has been demonstrated that the maximum time domain response of the platform after vibration reduction is 8.75 g (less than 50 g), and the maximum root mean square value of the power spectral density (PSD) is 1.82 g (less than 3 g). The designed secondary vibration reduction structure can serve as a reference for the design of vibration reduction in unmanned aerial vehicles. [ABSTRACT FROM AUTHOR]

As the core component of the automobile braking system, brake pads have a complex structure and high failure rate. Their accurate and effective state monitoring can help to evaluate the safety performance of brake pads and avoid accidents caused by brake failure. The wear process of automobile brake pads is a gradual, nonlinear, and non-stationary time-varying system, and it is difficult to extract its features. Therefore, this paper proposes a CNN-LSTM brake pad wear state monitoring method. This method uses a Convolutional Neural Network (CNN) to complete the deep mining of brake pad wear characteristics and realize data dimensionality reduction, and a Long Short-Term Memory (LSTM) network to capture the time dependence of the brake pad wear sequence, so as to construct the nonlinear mapping relationship between brake pad wear characteristics and brake pad wear values. At the same time, the artificial Gorilla Troops Optimization (GTO) algorithm is used to perform multi-objective optimization of the network structure parameters in the CNN-LSTM model, and its powerful global search ability improves the monitoring effect of the brake pad wear status. The results show that the CNN-LSTM model based on GTO multi-objective optimization can effectively monitor the wear state of brake pads, and its coefficient of determination R2 value is 0.9944, the root mean square error RMSE value is 0.0023, and the mean absolute error MAE value is 0.0017. Compared with the BP model, CNN model, LSTM model, and CNN-LSTM model, the value of the coefficient of determination R2 is the closest to 1, which is increased by 8.29%, 5.52%, 4.47%, 3.30%, respectively, which can more effectively realize the monitoring and intelligent early warning of the brake pad wear state. [ABSTRACT FROM AUTHOR]

The resonance of the gear-rotor system will produce a large number of responses that do not exceed the threshold value, resulting in structural fatigue failure and transmission failure, affecting its life and reliability. It is particularly critical to consider the temperature rise under high-speed and heavy-load conditions. Therefore, the research will take the main drive gear-rotor system of a certain type of aeroengine accessory gearbox as the research object, consider the influence of the temperature field on the natural frequency of the gear-rotor system, and take the difference between the natural frequency of the gear-rotor system and the excitation frequency (gear meshing frequency) as the performance function. The PC-Kriging and adaptive design of experimental strategies are applied to the thermal-structural coupling parametric model to analyze the resonance reliability and sensitivity of the gear-rotor system. For complex mechanical mechanisms, the method has better accuracy than other surrogate models and greatly saves the time of finite element simulation in reliability analysis. The results show that the natural frequency of a gear rotor decreases with an increase in temperature, and the natural frequency of different orders varies with the change in temperature. The influence of the sensitivity of different random parameters on the resonance reliability of the gear-rotor system is obtained. Reliability research on resonance failure of high-speed and heavy-load aviation gear-rotor systems considering random parameters under a temperature rise field has important practical engineering application value and scientific research significance. [ABSTRACT FROM AUTHOR]

To improve the efficiency and accuracy of reliability assessment for structures with small failure probability and time-consuming simulation, a new structural reliability analysis method (RCA-PCK) is proposed, which combines PC-Kriging model and radial centralized adaptive sampling strategy. Firstly, the PC-Kriging model is constructed by improving the basis function of Kriging model with sparse polynomials. Then, the sampling region which contributes a great impact on the failure probability is constructed by combining the radial concentration and important sampling technology. Subsequently, the k -means++ clustering technology and learning function LIF are adopted to select new training samples from each subdomains in each iteration. To avoid the sampling distance in one subdomain or the distance between the new training samples in two subdomains being too small, we construct a screening mechanism to ensure that the selected new training samples are evenly distributed in the limit state. In addition, a new convergence criterion is derived based on the relative error estimation of failure probability. Four benchmark examples are given to illustrate the convergence process, accuracy and stability of the proposed method. Finally, the transmission error reliability analysis of thermal-elastic coupled gears is carried out to prove the applicability of the proposed method RCA-PCK to the structures with strong nonlinearity and time-consuming simulation. [ABSTRACT FROM AUTHOR]

The seasonal dynamics and spatial distribution characteristics of surface runoff in Changbai Mountain simulated by the process model (EPPML), and the relationships between surface runoff and environmental conditions were analyzed. The results showed that the seasonal variation of surface runoff in Changbai Mountain presented obvious three-peak pattern, i.e., the lowest values in June and September, peak values in August (2.58 mm.d-1), similar to that of soil water content. Total trend of surface runoff for different vegetations in the growing season was in order of grass and shrub > coniferous forest > broad-leaved forest > mixed broad-leaved and Korean pine forest, highly correlated to LAI. Annual surface runoff in 1995 was estimated to be 0.203 m.yr.-1, mostly ranging from 0.0 to 0.246.m.yr.-1, accounting for 69.3%. The trend of spatially increasing annual surface runoff along with increasing altitude was obvious. The maximum annual surface runoff appeared in alpine grass (0.619 m.yr.-1), minimum in mixed broad-leaved and Korean pine (Pinus koraiensis) forest (0.081 m.yr.-1), others being alpine tundra, Betula ermanii forest, meadow, shrub, mixed spruce (Picea asperata) and fir (Abies nephrolepis) forest, Changbai larch (Larix olgensis) forest and broad-leaved forest. Vegetation and environmental conditions controlled the main trend of the spatial distribution of annual surface runoff in Changbai Mountain. There was very strong negative exponential correlativity between annual surface runoff and LAI (R2 = 0.857). The more LAI, the more literfall, the more precipitation intercepted by litter, thus, the less surface runoff. Annual surface runoff was highly negatively correlated with air temperature and total solar radiation (R2 being 0.965 and 0.836 respectively), however, it was highly positively correlated with precipitation, relative humidity and wind speed (R2 being more than 0.950). And annual surface runoff was also strongly correlated to soil characteristics.

In this paper, the a ecosystem productivity process model for landscape (EPPML) reflecting carbon and water cycles of system was described and discussed. In EPPML, leaf area index (LAI) that greatly influenced vegetation productivity was received from remote sensing images, the spatial distribution and temporal dynamics of net primary productivity (NPP) and evapotranspiration were simulated. Geographical information system (GIS) was used to process, analyze, and display spatial data. Thus, the studies on physiological ecology could be extended, and converted from small scale to larger scale. Using EPPML, the vegetation productivity in Changbai Mountain Natural Reserve in 1995 was simulated. EPPML could well and truly simulate the NPP of main vegetations in the natural reserve. NPP was estimated to be 0.680 kg Cm.-2.yr.-1, mostly ranging from 0.105 to 1.241 kg C.m-2.yr.-1, accounting for 82.1%. The highest NPP (1.084 kg C.m-2.yr-1) appeared in mixed broad-leaved and Korean pine forests. The total NPP was estimated to be 1.332 x 10(6) t C.yr-1. The highest total NPP appeared in mixed broad-leaved and Korean pine forests and spruce-fir forest, which were 0.540 x 10(6) t C.yr.-1 and 0.428 x 10(6) t C.yr.-1, respectively. The seasonal variation of NPP appeared obvious single peak with peak value in July (6.13 g C.m-2.d-1). The most NPP accumulated in the summer, which was 0.465 kg C.m-2, secondly in the spring, and least in the winter.

Based on the data received from remote sensing images, the spatial distribution of annual net primary productivity (NPP) was simulated by the process model (EPPML), and the relationships between annual NPP and environmental conditions were analyzed. The results showed that NPP in 1995 was 0.680 kg C.m-2.yr.-1, mostly ranging from 0.105 to 1.241 kg C.m-2.yr.-1, accounting for 82.1%. The highest NPP (1.084 kg C.m-2.yr.-1) appears in mixed broad-leaved and Korean pine forest. Environmental conditions decide the main trend of the spatial distribution of annual NPP (Carbon) in Changbai Mountain. Soil water content had a negative correlativity with NPP, and the correlation coefficient (R) was -0.65. Therefore, water was sufficient for the growth of plants in Changbai Mountain. NPP was highly correlated with LAI (R = 0.81). When LAI was greater than 4-5 m2.m-2, NPP became saturated. NPP was also highly correlated with canopy transpiration (R = 0.77). The response of NPP on environmental conditions, LAI and canopy transpiration in Betula ermanii and broad-leaved forests were different from those in other vegetation.

The study used EPPML, a biological geochemistry cycle model that was built, to simulate the carbon budget for ecosystems in Changbai Mountain Natural Reserve. The results indicated that the annual net primary productivity [NPP (carbon)] of the natural reserve was 1.332 x 10(6) t.a-1. The annual NPP of mixed broad-leaved and Korean pine forest and spruce-fir forest were maximal, 0.540 x 10(6) t.a-1 and 0.428 x 10(6) t.a-1 respectively. The area and productivity of the two stands were maximal in Changbai Mountain, therefore, the simulating productivity of the two stands most greatly affect carbon cycle and carbon budget of the natural reserve, and the veracity of the former decides the security of the latter. To sum up, not only did the simulations accord with routines in the relative comparisons between different vegetation belts and climate belts in the whole natural reserve, but also was exact in the absolute comparisons with very disperse data from field survey. Vegetations in the natural reserve had evident carbon sink functions, mainly exhibiting in the increasing of carbon, about 1.058 x 10(6) t.a-1. The annual carbon of mixed broad-leaved and Korean pine forest increased greatest (0.452 x 10(6) t.a-1), secondly spruce-fir forest (0.339 x 10(6) t.a-1). The two stands played crucial roles in the carbon sink for Changbai Mountain, others being Changbai larch forest, broad-leaved forest, meadow, shrub, alpine tundra, subalpine Betula ermanii forest and alpine grass. In 1995, the decomposing carbon of soil organic matter was 0.169 x 10(6) t.a-1 higher than the littering carbon in the natural reserve. There was accumulation of organic matter in the meadow soil and shrub soil. The decomposition and accumulation of soil organic matter was in the nearly balancing condition in the alpine tundra soil and alpine grass soil. The decomposition of organic matter was as one and a half time or double as litterfall in the arbor forest soil.

Ecosystem management is a synthetic applied ecology concerning ecosystem management theories, practical technologies, relevant policies and management strategies. It is not only an urgent need for the sustainable development of human society, but also an important tendency and scientific task of ecosystem management to develop integrated studies on models of global or regional scale ecosystem management and the relevant scientific problems. For this reason, we systematically expounded a series of important ecological topics, such as the synthetic evaluation and ecological mechanism of the services, sustainability, complexity, and indeterminacy of ecosystem, the ecological basis of natural resources conservation, ecosystem health, and the rehabilitation of degraded ecosystem, basic ecological processes for ecosystem management, theories and practice on adaptive management of ecosystem, ecosystem network study, monitor, and achievement integration, as well as synthetic special topic studies on regional scale ecosystem management etc. Research advances and tendencies of these topics at home and abroad were also reviewed.